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Voice and avatar face recognition with focuson familiarity and recall accuracy for use in a

contact book designed for illiterates -Worksheets

Alex Patrick Hauge & Christian Bødtkjer Jørgensen

May 2013

Contents1 Introduction 2

2 Theory 22.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22.2 Voice Recognition Theory . . . . . . . . . . . . . . . . . . . . . 2

2.2.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 72.3 Facial Recognition Theory . . . . . . . . . . . . . . . . . . . . . 72.4 Illiterate Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.4.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 12

3 Implementation 133.1 Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133.2 Implementing the Design . . . . . . . . . . . . . . . . . . . . . . 173.3 Avatar Creation . . . . . . . . . . . . . . . . . . . . . . . . . . . 183.4 Sound recording . . . . . . . . . . . . . . . . . . . . . . . . . . . 203.5 Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233.6 Database . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233.7 The Final Product . . . . . . . . . . . . . . . . . . . . . . . . . . 24

4 Test Design and Results 304.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 304.2 Voice Recognition Test . . . . . . . . . . . . . . . . . . . . . . . 30

4.2.1 First Low Fidelity Test . . . . . . . . . . . . . . . . . . . 30

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4.2.2 Second Low Fidelity Test . . . . . . . . . . . . . . . . . 364.2.3 High fidelity test . . . . . . . . . . . . . . . . . . . . . . 38

4.3 Avatar Recognition Test . . . . . . . . . . . . . . . . . . . . . . . 434.3.1 Low Fidelity Test . . . . . . . . . . . . . . . . . . . . . . 434.3.2 High Fidelity Test . . . . . . . . . . . . . . . . . . . . . 464.3.3 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . 49

4.4 High Fidelity Test of Interface . . . . . . . . . . . . . . . . . . . 504.4.1 Test setup . . . . . . . . . . . . . . . . . . . . . . . . . . 50

4.5 Test Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 524.5.1 Subject 1: Male, 25 . . . . . . . . . . . . . . . . . . . . . 524.5.2 Subject 2: Male, 24 . . . . . . . . . . . . . . . . . . . . . 534.5.3 Subject 3: Male, 24 . . . . . . . . . . . . . . . . . . . . . 534.5.4 Main Findings from Subjects . . . . . . . . . . . . . . . . 544.5.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . 55

1 IntroductionThis worksheet is a companion document to the paper "Researching feasibility ofusing Voice Recognition and Avatar Face Recognition in a Contact Book". It con-tains explanations for theory used, test design and results and the implementationof the accompanying product. Because this is a companion document, there havenot been made an effort to seam it all together which might result in the documentseeming messy.

2 Theory

2.1 IntroductionIn this chapter the theory behind the choices will be discussed. Each sectioncontains a quick introduction and then some information about the sources used.

2.2 Voice Recognition TheoryA feature in the contact book includes using a button which plays the voice ofthe contact, thereby helping them recognize the person. In this section there isprovided a description of voice recognition.

In our daily lives most of our social interactions happens with combining in-formation from both the face and the voice of the person in order to identify himor her. Such as when meeting a person on the street or seeing one in the television.

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One form of interaction that does not use the combination of facial and voice in-formation is interaction through the mobile phone or over the net by using chatprograms [3]. There is a reason why the brain combines both visual and auditoryinput for identifying a person. As is described in the paper by Campanella andBelin [3] there is evidence for the integration of information from face and voicein the human brain. A lot of research has gone into investigating the integrationof sound of speech with the visual feedback from the articulating faces. This re-search is based on the interaction between speech and visual articulation, less isknown about other types of facial and vocal integration of information. Using fa-cial and speech input it is possible to learn a lot about a person’s identity [3], suchfeatures are gender, age, body size(vocal tract length) or even emotional states,information that is of great importance when socializing with other people.

When recognizing a person when socializing, both voice and facial featuresrely on each other for the most precise identification of the person. As describedin the paper by Joassin et. al. [7] it showed that when identifying a person, voicerecognition was easier when simultaneously presented with the correct face andof greater difficulty when presented with a face not sharing the same identify.This shows that when listening to a voice, the listener cannot ignore a face whentrying to recognize the voice [7], this was only the case for familiar voices assome experience is needed to identify a certain person. In [7] they performeda test using a setup of faces(F) and voices(V) and voice-face association(VF),each test-participant had to identify the persons included in the test after havingfamiliarized themselves with the four identities. The results of this test showedthe relationship between facial and voice recognition in relation to time. Voicesproved to be identified at a slower rate than faces or voice-face associations; thepattern was the same in response to error rate [7]. Even though voice recognitionis slower, it provides important information for identification and for the combinedidentification using face and voice.

When you talk on the mobile phone, you no longer have facial features foridentification but have to rely on auditory information from the speech alone.When there no longer is any visual feature, you will start by trying to identifythe callers by gender, young or old, familiar or unfamiliar and even the emotionalstate [9]. This information is derived from one single audio stream, it can be di-vided into two sections the recognition of the person and perception of what theperson is saying. In order to figure out if sound is usable for identification overa phone it’s also important to look into the importance of changing content of asentence and most important how the sentence is said. In the paper by Lander et.al. [11] they investigate the effects of what is said and how it’s said when iden-tifying an unfamiliar person. When a person speaks, the mechanics behind thespeech does not only produce the sound of the voice but also the movement ofthe face, which the brain takes advantage of [11]. This makes the visual infor-

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mation of the face important for speech perception, for both cases of loud noisesand emotion perception. This said it is also possible to identify a person onlyfrom the face or the speech of the person. Some investigation indicates that forfaces movement can also serve as an additional cue for face identification [11]. Ingeneral it supports that there is a cross modality when identifying a person, usingthe combination of both speech and facial information, combining them for anidentification. The cross modality has been shown in experiments [11] where theparticipants were tested on their ability to match identify from a silently movingface to a voice and the same for voice to face. It showed that it was possible toidentify, as long as the word or sentence used was also used during training. Thissuggests that the sequence of the speech is an important cue for matching face andvoices [11].

The fact that the sentence is of importance when matching face and voices isnecessary to keep in mind when design the tests, in order to keep the variables forthe recognition as close to constant as possible. It is still possible to identify a faceto speech even though the sentence is not the same as described in [11], this sug-gest that identify matching is not solely tied to the linguistic content, but that thenonverbal variation of the speech is sufficient to determine the identity. Featuressuch as pitch, loudness and speaking rhythm provides important information foridentifying as well as if the sentence is a question or not and the punctuation of thewords and last attitude and emotions [11]. These features will all aid in the identi-fication of the person at hand, some more closely tied to the facial expression thanothers. In [11] they perform a number of tests for these features in relation to faceto voice matching and visa versa, these test procedures are used as inspiration fortesting the feasibility of identifying an unfamiliar avatar with an unfamiliar voice.

For their test setup they use two sets, one with face-to-voice(FV) identitymatching and one with voice-to-face(VF) identity matching, but using videotapesof the face and voice, giving motion to the target. This is not used for the paperwhich this chapter is written for, instead static avatar faces are used for the visualinformation. In order to get both sides, the use of voice-to-face matching andface-to-voice matching is used. In the paper [11] they do a total of six tests on thedifferent features mentioned above, to find its impact on identity matching. Theresults found by [11] is useful for the design of the application, as it helps givea better understanding of the impact on identity matching by different features.In the first experiment they found no sign of impact by changing sentences, butchanging the manner had an effect. Sentences spoken with the same manner hada significant better identity matching. This shows that the cross-modal identitymatching is more tied to the manner than the content of the sentence [11].

For this test there were no differences between the matches FV and VF. Thethird experiment was regarding the effect of conversational speech and clear speech,

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they found no significant difference between the two [11]. They found that achange in manner at this stage also had a great impact on the identity matching.The fourth experiment was made to find the effect of conversational speech andcasual speech, as it can change their speaking rate. In the fourth experiment theyagain found the manner of the spoken word to have a great impact on the identitymatching.

It showed that matching conversational to conversational sentences was sig-nificantly better than in the case of casual to casual matching. In the fifth testthe look into the effect of artificially slowing the voice, which showed to have noeffect on the identity matching. The artificial slowing was done in such a waythat the fundamental frequency was kept the same. The final experiment involvedspeeding speech and conversational speech. From this experiment it showed thatthere was no effect of changing tempo. These results give a better understandingof the impact different features can have on identity matching.

A place that has used identification by voice is the court of law, when trying toidentify a person by voice from people that was close to the incident or in cases ofthreats over the phone [5,12]. The interesting factor in use of voice recognition incourt is the effect of time between the crime and when the witness has to identifythe accused. In a case described by McGehee [12] a positive identification of thedefendants voice almost three years after the incident, was accepted by the court asmaterial evidence, but what is the effect of time when recognizing an unfamiliarvoice. When hearing it can be very difficult to identify a sound of a specificcharacter and hard to assign them to what has caused it. Several features of soundcan be misinterpreted, such as the direction of the sound as well as quality andintensity. A simple experiment described in [12] shows how hard it is to identifythe character of the sound as well as cause.

The experiment was performed by the teacher striking a tuning fork beneaththe desk, then the students one by one had to try and identify the sound source.Only 2 out of a hundred guessed correctly, showing that the judgment when de-termining a sound source is highly prone to error. Franches McGehee [12] madean experiment to find out the impact of time. A number of students were tested,each first got a paragraph of 56 words read to them from behind a screen and toldto listen carefully as they will be tested later. The voice presented for them is usedfor training the test participant. The intervals of time that is used in the test is 1,2 and 3 in days, weeks and months. The interesting results from trying to iden-tify the voice after certain time intervals are shown below [12] in Table 1. Thetest participant was presented with 5 voices, reading the paragraph from behindthe screen, and then having to identify the previously heard voice. For the test atotal of 189 men and 155 women were tested. These results are achieved usingunfamiliar voices, but give a good view of the decline in recognition of unfamiliarvoices over time. When talking to a person over the phone, you sometime will en-

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Time Interval Percentage Correct1 83.0%2 83.0%3 81.0%

Weeks1 80.8%2 68.5%3 51.0%

Months1 57.0%2 35.0%3 13.0%

Table 1: Table describing the correct recognition of a voice with different timeintervals.

counter several voices depend on the place and situation. When there is no longerone single audible track, stream segregation takes place in order to focus on thevoice needed. So far the theory has only covered cases with unfamiliar targets, butas this project will use familiar target primarily its necessary with further infor-mation. In the paper by Rochelle S. Newman and Shannon Evers [14] they lookinto the effect of familiarity of a person when trying to recognize the voice in astream.

The test was setup with 67 students that participated in the test, 24 of thesewere following a class with a professor that is not the target. The last 44 studentswill have the target speaker as the professor for the course they were following.The test is then performed later in the semester [14]. This is done to learn andthereby familiarize them with the target. The stimulus for the test was the pro-fessor reading both a list of words and a story passage in the style he normallyspoke when teaching. The group of test participant would be divided into two,one where they are told who they are listening to (explicit knowledge group) andthe other half were not (implicit knowledge group).

As is stated in [14] the familiarity effect is not transferred from fluent speech toa list of words. Beside the target professor, a second male recorded the same pas-sages and words. The target and non-target voice was then intertwined, for the testparticipant to track. They found that people in the explicit knowledge performedthe stream segregation with fewer errors in form of missed words compared tothe implicit group. They found no significant effect from familiarity that the onegroup had as they did not perform significantly better than the group that was not

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familiar with the professor when tracking the voice. This shows that simple fa-miliarity that all gained in the test as they were given one voice in the beginningto follow is enough to aid in the stream segregation compared to a whole semesterof familiarity [14].

2.2.1 Conclusion

In general when identifying a person from the voice, it is a process that is closelytied to the visual input in form of facial expression and movement. It is possibleto identify without facial input, but with sound there are several features that playa role in how accurate the identity matching is. Such as the manner of how aword is expressed which include pitch, tempo, timbre all part of the change inthe voice that can occur from emotional states and more. Beside these featuresthe effect of time between hearing the voice and trying to identify, is crucial asthe accuracy declines to around 50% within 3 weeks for unfamiliar targets. Thisis important to take into account, as this project is about creating a contact bookfor illiterates. But since the voice is not to stand alone, but is aided by an avatarimage of the person thereby using cross-modality, it should decrease the error rateon identifying the person in the contact book.

2.3 Facial Recognition TheoryIn this section some relevant parts of face recognition will be discussed. Themost relevant ideas throughout the current research is the ideas of feature-specificperception and holistic perception. These two functions as different explanationsof how human beings transfer the information of the collection of feature in theface. The feature-specific perception is explained by the observer scanning a faceexplicitly for local features, such as eyes, eyebrows and mouth, and using thesefeatures as individual parts to recognize the face. Holistic perception is the otherway around, by having the observer see every local feature as a whole percept,which is then a collection of all the features that makes a face, including hair,chin, etc.

Belle et. al. [2] took a look at the differences of these two views and testeda brain damaged patient who suffered from prosopagnosia (impaired face recog-nition skills) and a control group. The test measured performance in differentsituations where certain parts of the face was masked out, as to render the holisticperception inert or vice-versa with the feature-specific. They compared averageaccuracy and speed of the control group with the patient, which showed that thepatient performed clearly worse than the control group in two cases. The patientwas much slower in each task and had less accuracy when showed a full face

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or a masked face. They were shown either a full face without hair and ears, awindowed face which only showed one feature or a masked face in which one ormore features is masked out. The interesting thing about this test is that the con-trol group drops to the same accuracy as the patient when tested on the windowedpart. They also did an experiment to see if the size of the mask mattered whichthey found out it did not.

The different features found in the face also combines to express emotions,show attention, gender, age and other social information. Yueting Sun, XiaochaoGao and Shihui Han [15] experimented with this extra social information by tryingto see if there was a difference in performance when measuring this informationbetween gender. They used Event-related potentials to test for performance inboth female and male participants, by showing them pictures in which they had totell face orientation(low-level perceptual feature) or e.g. gender(high-level socialfeature). The results show that females has more attention towards the socialfeatures and performed better throughout the trials.

Steven G. Young et. al. [17] also looked at the social information and lookedfor cross-race/same-race differences when recognizing faces. The hypothesis isthat people who have never seen another race of humans will not have been trainedto be as good at differentiating between faces as people who have had exposureto that race. They review current research and argues for future research in thearea. In conclusion they argue that a collected framework which seeks to unifythe current theories about the cross-race/same-race problem will further enhancethe research and might provide clear results.

Robert G. Franklin Jr. and Reginald B. Adams Jr. [8] also examined the re-lationship between facial features and deeper emotional meaning being given tothese. The participants that took part in their experiment were shown a randomseries of faces that they would have to remember for a later recall task. The par-ticipants had to find a face they had seen before in a series of a mix of distractorsand faces they had seen before. The results was supporting their hypotheses, a)individual differences in the ability to decode emotional messages from expres-sive faces would be positively associated with the ability to encode and subse-quently remember a separate set of neutral faces in the same participants, and b)that stimulus-level differences in the extent to which a separate group of raters as-cribed emotionality to these same neutral faces would also be positively associatedwith face memory.

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2.4 Illiterate Theory

This project is concerned with illiterates and the difficulties that they encounter,when interacting with new technology through the standard user interface. Asmost user interface applies text to inform the user of the different functionalities,this means that illiterate people have great difficulty with understanding the inter-face as they cannot read. During this chapter the focus will be on illiterates andthe challenge of designing user interfaces, which are independent of text.

When learning to read and write, it also adds to one’s ability to match bothbasic units of language to words as well as the smallest semantically units in thewritten language, to internal system for the language [4]. As described in thepaper [4], it seems that the beginning of the oral language is also affected by theprocess of learning how to read and write, indicating that both the oral systemand that responsible for reading and writing interacts. For illiterates this mean asindicated by studies [4] that their ability to deal with phonetics, that is units ofspeech, is not dealt with automatically but is a result of learning to read. Withthis disability most illiterates has to find another way to deal with the problem ofinteracting with computers, than literate people.

A case that most illiterate people have to deal with, especially in the west-ern world is withdrawing money from an ATM machine, as most interaction withATM is through a text based interface. In the article by A. Thatcher, S. Mahlanguand C. Zimmerman [16] they investigate how an icon based interface can be cre-ated for illiterate on the ATM. As they describe there have already been suggesteda number of alternatives for the normal text based interface. An example is a sys-tem for blind people that also have a difficult time interacting with the interfacethat they cannot perceive, as well as systems for aged people [16]. The problemfor both these groups is the written interface just as it is for illiterates, some in-vestigation has gone into using voice recognition as an alternative interface forblind people. This speech based interface could also prove useful for the illiter-ates. The problem of a speech based interface is when used in a country that ismulti-cultural, causing a lot of different dialects. Beside a speech based interfaceanother possibility is an icon based interface for illiterates. As is explained in thepaper [16], icons prove to generally lead to a faster recognition when learning anew system and are remembered easier than the equivalent sentence that wouldhave replaced the icon. This is due to that the icons may be stored both in thevisual and verbal memory.

In the paper [16] they chose to follow a user centered design, focusing on themost common functionalities of an ATM machine, such as withdrawal. In order totest their interface design a test was made testing three different ATM interfaces

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with two groups, one literate and the other illiterate. The three different designsare a text-only interface, icon-only interface and a text-and-icon interface [16].Each design is randomly assigned to each test participant, and asked to perform atask. For the test 25 illiterates were used and a group of 29 literate subject. Bothof these groups are familiar with the use of an ATM machine and have had a bankaccount for a year or more. None of the people in the groups speak English as thenative language [16].

In the test of the three interfaces [16] they found that a number of people with-drew from the task before finishing it, both from the illiterate and literate group.For the test of the performance results from the task, the result was measured asthe time it took from they started until they finished the task at hand.

When looking at the result from the paper [16] regarding transaction perfor-mance of the three different interfaces and two groups, there is a significant dif-ference between the literate and illiterate group. The two literate groups that hadtext design and text-icon showed to be significant faster than the three illiteratesgroups with text, text-icon and icon. Within the illiterate group, people performedfastest in the interface with text and slowest in the icon interface [16]. Thesedifference was not statistical significant but worth noting. For both the illiterateand literate groups there was no significant change between the text and text-icondesign. As might have been expected the literate group proved slower at iconinterface compared to text interface.

The reason why illiterates proved faster in the text design might be due to thedesign of icons and the conflicts with the general icon design used in ATMs. Thereason could also be that the illiterates has learned to recognize certain words,relating its function to the visual construction of the word. This is useful for thedesign of the app, that it might not be bad with text in the interface, although theultimate goal is to create a design efficient enough to translate the informationwithout words.

Beside ATMs, illiterates also have to deal with the interaction design of mobilephones, which has a very text based interface design. In the paper by Kristin DewEt.Al [6] they research the subject of how to create an alternative interface formobile phones, for illiterates. Normally when illiterates deal with the standardinterface designs from mobile phones, they find workaround in order to cope withthe text based interface [6], for example by using memory patterns. The goalfor Kristin Dew Et.Al [6] was to create an interface for illiterate mobile devices,within the United States. The product that they develop [6] is a program that runsin the background not visible to anyone, thereby leaving the interface as standard

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instead of modifying it. By not modifying the interface, it helps to not stigmata theilliterates and at the same time help support learning of reading. The program is anon-demand playback, meaning that it plays back text-to-speech, activated by usinggestures. This feature will read words allowed from text messages and more. Thishelps the illiterate to navigate and use functionalities easier at a discrete manor.This is still a work in progress, but the way of dealing with illiterates problem ofnavigating a mobile interface by using a playback of text is a both useful conceptand discrete. Sound can help with closing the gap that illiterates have with text,in the project this is used to help them identify persons in the contact book of amobile phone.

The study made by Zereh Lalji and Judith Good [10] is concerned with investi-gating how to design a mobile phone for illiterates, that include their expectationsand a user designed interface and what they might need for support. Performing auser centered design is useful as a designer does not know what an illiterate mightneed as well as the impact the experience of an illiterate person has on interactingwith an interface. The study by Zereh Lalji and Judith Good was divided into twosections one concerning the different features that illiterates would like as wellas design, the second is related to the use of the phone by illiterates and how thefeatures can be incorporated.

By interviewing a group of illiterates they try to identify the needs of illiterateswhen using a mobile phone. The illiterates found that they were not educatedenough to use a phone, some even sold it when given one [10]. When asked forreasons for wanting a mobile phone, they tell that they want to improve businesses,contact with families that might live apart from them. When dealing with wordsand numbers in the case of using a phone, the illiterate’s ability to associate andrecall was well developed. To deal with saving phone numbers, the most importantnumbers was memorized and the other written down in a telephone diaries, orused the recently called function. The way they identified the numbers to a personwas by features like the style of the handwriting, page number, markers or inkcolor [10]. Some of the illiterates was not able to tell time but used the arms on thewatch to tell when they needed to be somewhere. This gives a better understandingof how they deal with the different task when interacting with text and numberson a phone, information useful when designing a contact book for illiterates. As isexplained in the paper [10] they found a big gap between the western icon designand what was understandable when shown to illiterate people not living in thewestern civilization. So dependent on what country or region the design is madefor it has to be adapted to that culture. The people in this study are not onlyilliterate but also illiterate in technology causing some difficulties that might notbe the case for illiterates in more developed countries, but need to learn this. Aninteresting feature that was incorporated into their high fidelity prototype to deal

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with the difficulties that illiterates had with learning and coping with the use ofthe phone, was a voice instruction that helped them navigate and use the phone.

In the article [13], the problem of creating an interface for illiterates on themobile phone is dealt with by creating an interface using icons, audio and cartoonsto communicate the information. The interesting section of this article, is how theproblem of assisting the illiterates handling new programs, is handled. When anapplication is opened a smart video dramatization is launched, which illustrateshow it works. This might prove to give a better adaptation for different culturesas video is a powerful tool, and better can convey different cultural expression.

Another aspect of how illiterate cope with using a mobile phone memory,in this study by Syed ishtiaque Ahmed, Maruf Zaber and Shion Guha [1] theytest and interview 15 illiterates from Bangladesh who are not trained in digitaltechnologies as well. Each of these 15 subjects is required to have used a mobilephone for at least 1 year. They found that all the participants would use the calllist, which include the out and ingoing calls, and when saving the calls it wassaved on the memory of the phone [1]. There were 13% of the participants thatwould not make call for them self’s and of these there were just 47% that saved thenumbers. By looking at this it shows that they use a system of the last called as thecurrent contact book is not efficient enough for illiterates, as they use the call listinstead. Besides using the call list to locate a contact, they also found a number ofother methods that the illiterates applied. One method was to memorize the lastthree digits of the phone number; this causes some problem since more than onenumber can have the same three digits [1]. Others were dependent on getting theircontact saved in the contact book, often with help from others; by having themin the contact book they would remember positions of the contact in the list. Avery different strategy that was applied was trying to memorize the contacts nameas an image, using the way the names was put together with letters as a figure.These also had help save the contact in the contact book before applying the tacticof creating images from names. The last tactic that they found was to use thefrequency of letters, by memorizing the image of different letters. The illiteratesusing this tactic would then search the contact book for a contact with a specificfrequency of letters. An example of this could be the name "Lotte" with two "T"’sin it [1].

2.4.1 Conclusion

The information of how the illiterates deal with the phone [1] is useful when de-signing a contact book, as it gives an idea of how the illiterates deal with the differ-ent obstacles of the interface, and at the same time what problems they encounter

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using the phones memory. Finding a way of creating an interface that would makethese problems obsolete would increase the usability of the way the illiterates usethe contact book. In general the icon interface that needs to be created needs to beadjusted to each culture as the norms are different, as the semiotics are differentwithin cultures. If a pure icon based design is better for illiterates then one com-bining the two is hard to decide, ideally an icon based interface should be able toconvey all information needed if created right according to culture and more. Butat the same time using text combined with the symbols also help with the learningprocess of words for the illiterates.

3 ImplementationWhen creating the contact book for the illiterates, the knowledge of how illiteratesuse mobile phones has to be combined with the design of the contact book. Duringthis chapter there is given a description of the design that lead to the prototype aswell as the implementation of the design.

The success criteria for the implementation are described below:

• Functional interface.

• Basic functionality of a standard contact book.

• Creatable avatars.

• Record incoming/outgoing calls.

To implement the contact book for mobile phones, it is necessary to choose whatoperational system (OS) to develop to. For this project the OS that is developedfor is Android. In order to write code for Android OS, the eclipse environmentis used as a base for coding Java and Xml. To develop efficiently, the code is ac-cessible through GitHub, allowing several people to code simultaneously. For thedevelopment the Android SDK is used together with the ADT plugin for Eclipse.This setup will serve as the base for the development environment.

3.1 DesignIn the process of designing the application that should work as a contact book itis necessary to keep in mind the situation that illiterates are facing, not being ableto read words. This means that an ordinary interface with text is insufficient. Thedesign during this chapter is based on the knowledge of how illiterates interactwith mobile phones. The first step is to determine the needs and how to deal with

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the problem that illiterates have. The way that the illiterates gap is tried fixed, isby using an avatar created by the user to work as replacement for the normal textinterface with just a name and number. To further improve the recognition of thisavatar a playback function is tried implemented, but due to hardware restrictions itwas not possible, playing a period of conversation from the last call to that contact.These two ideas is the base of this prototype contact book.

To better understand what is needed to design the contact book, a brainstorm-ing of different functionalities was performed in order to determine the needs.Inspiration is also derived from looking into how the contact books of newersmartphones are designed. Below in figure 1 is a flow chart of the different func-tionalities that was derived in the process. The functions displayed in figure 1 are

Figure 1: Flow chart of the different functionalities.

those intended for the contact book, as this is a proto-type the modify contact isnot implemented. These functionalities needs to be incorporated into an interfacethat can manage the needs required for the functionalities to work as intended.The functionalities and their relations are going to serve as a base for creating theinterface. The design of the interface containing the functions described above, isdivided into four main screens:

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• Display of contacts.

• Add new avatar.

• Contact information.

• Search.

This first screen is the one you will enter when opening the contact book, contain-ing all the contacts and two buttons leading to the "search" and "Add new avatar"screen. The structure of this interface is visualized in the concept drawing in fig-ure 2. As is displayed in figure 2, the display of the contacts is made into two

Figure 2: The Start screen of the contact book

columns with the possibility of scrolling up and down through all the contacts.Each contact in the grid has the avatar displayed for that person as well as numberand name. The reason for this is that as described in the paper by Ahmed et. al. [1]one of the strategies that illiterates use when navigating a contact book is remem-bering the last three digits. In the final design the names are not shown in the gridonly the phone numbers. By using the number the design supports their strategyused when navigating a contact book. The next screen is the one containing theinformation of a specific contact, which will show when pressing the contact onthe grid, you want to view. The design is shown in figure 3. As is seen in figure 3,

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Figure 3: The information screen for the contact

this screen is divided into three sections. The first holds the avatar image, nextfollowed by the button for playback and then the name and phone number. Inthe final design there is added a button with a cross, positioned to the right of thesound button. This button will handle deleting the contact. The name and numberwhen pushed will perform the call to the contact. The next screen design is for the"Add new avatar" interface, this is shown in figure 4. The structure of the interfacein figure 4, is divided into a number of sections. In the top, the ability to createthe avatar of the contact is placed. Each arrow will change a feature of the avatarthereby making it possible to create an avatar representing the subject. In the finaldesign the accessories are displayed in a grid instead of one box. The numberof features in each category will help make it possible to create an even moreunique avatar. When the save button is pushed, a follow up screen will emerge.This screen will allow the user to enter name and phone number and finalize thecreation of the contact, which will be saved and showed in the entry screen. Thelast screen is the one concerning the search function, this interface is displayed infigure 5. In figure 5 the search interface is displayed, similar to the entry screen,it contains a scrollable grid with the contacts in. This grid will update as the userselect and deselect different features in the search for the specific contact. Anexample is when clicking the button controlling the feature that is glasses; it will

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Figure 4: The "Add new avatar" screen, when saving a follow up screen will showallowing the name and phone number to be entered.

either remove all contacts with glasses or all those without dependent on the stateof the feature. This way of searching should help the problem that illiterates havewhen searching a list of contacts in the standardized contact book of smartphone.As illiterates can’t search for names as they are not able to read, it allows themto search for the visual features of the avatar they have created to represent theperson in mind.

3.2 Implementing the DesignIn this section of the chapter, the implementation of the design described in theprevious section is described. A general description of the code design is used tobetter describe the code and structure of the program that supports the function-ality mentioned in the previous design chapter. Interface The first element thatis covered is the code design for the interface implemented in the project. Theinterface is coded in two manners, one using Xml language supported by AndroidSDK and the other in Java alone. Java and Xml can also be combined. The Xmlalone provides a fast and easy way of creating an interface using different layouts,the drawback with pure Xml is that it does not support dynamic interfaces on itsown. For a dynamic interface you need Java alone or combined with Xml, this

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Figure 5: The interface of the search screen, containing a scrollable grid andfeature selection for search.

allows changes in real time. The interfaces are constructed using a number ofdifferent layout managers that allow for arrangement of icons, buttons and moreinto the layout needed. The interface is built within each activity, each activityworks as a screen giving a surface to display the buttons and graphics on for theuser. To get a better understanding of the entire frame of activities and the relatedinterfaces, which provides the base for the functionality, a flow chart has beencreated as displayed in figure 6. As is shown in figure 6, it’s possible to go fromone activity the other, providing the general structure of the application. Withineach activity is the interface programmed, connected with an underlying code thatsupplies the functionalities for the different buttons in the interface.

3.3 Avatar CreationIn the avatar creation screen it is possible to cycle through variations of hairstyleand color, noses, eye color and shape, mouths, chin builds, gender, skin colorand if the person should have glasses or not. The amount of variations differ toincrease variety though optimally, more variations is better. Given the currentamount of feature variations, a very high amount of combinations become pos-sible. It ended up looking as in figure 8. In figure 7 a quick flow chart over the

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Figure 6: Flowchart of the activity setup.

components included as functionality can be seen.

Figure 7: Flowchart over avatar creation.

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Figure 8: Avatar creation screen in final application.

3.4 Sound recording

In this section the implementation design of the playback feature is described.This design is split in two parts, one concerning the playing of the recorded voiceand the other with regards to the recording of the voice during the phone call.Due to restrictions in the API and phone setup, the function created by androidfor recording phone calls was not accessible on the tested phones. The design inthis chapter works as intended but the one hurdle that the tested phones are notpermitted to access the android function called voice call. Both the playing audiopart and the recording audio are tied together by the database that is explainedlater in the chapter.

As described in the design section, it is possible to play the voice of a contactby pressing a button within the avatar info screen. This button when pressed willtry to locate a sound file in a specific file on the phone; this file will have the samename as the number of the contact. To get a better understanding of the designbehind the playback function, a flow chart is created in Figure 9. When setting upthe playback function there is first created a button as seen in figure 9, to this but-ton an "OnClickListener" is assign which listens for any activations of the button.If the button is activated it will create a "MediaPlayer" that will handle playing theaudio file. Before starting the "MediaPlayer" the recorded sound file needs to be

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Figure 9: The flow chart of the sound button for the playback function.

located on the phones memory. The audio file when recorded as is explained lateris saved as the phone number of the person that is called. Knowing what folderthe files are stored in, it’s possible to search for the file by acquiring the phonenumber of that contact through the data base and use it as a part of the addressfor the audio file. When the audio file is located it is set as the "DataSource" forthe "MediaPlayer", this allows the "MediaPlayer" to prepare and start to playbackof the sound. Before the audio file can be played it needs to be recorded. Thisdesign is made to record directly from the uplink and downlink in the phone call,recording both incoming and outgoing conversation. It was discorvered at a latestage in the implementation that this functionality provided by android was notaccesable for all phones as some phones had blocked it. The design is still madewith this function as it is what is intended for the product, instead of having to doa low tech and very indiscrete recording over the speaker whenever talking with aperson. This is not an option, as there should be no signs when using this applica-tion, that can cause illiterates to feel different than the population. To get a betteroverview of the structure of the record audio design, a flow chart is displayed inFigure 10 explaining the structure. The whole process of recording the voice dur-ing the call starts when the record function as depicted in Figure 10 receives an

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Figure 10: The flow chart of the sound record design.

intent. The intent is specified in the manifest file, where an intent filter is appliedto this function only letting it receive specific intents. If the intent is not null itsaves the phone number of the person that is calling or called which goes intothe function that sets up the path for the memory of the phone, for later to workas the address of the newly recorded file. The essence of the record function isthe "Telephone manager" the applies a listener that listens for changes in the callstate of the phone. When the call state of the phone enters the "Offhook" it startsrecording, as it indicates that the call is in progress. The two other states "Idle"and "ringing" both ensure that the call is stopped as a call is no longer in progressat that state. The result of this function, when the start recording is called, is anaudio file saved in a specific directory with a file name similar to the phone num-ber of the called person. This allows for the playback function when in the avatarinfo screen to play back the sound knowing that the audio for this contact, hasthe path with the phone number as the name of the file. At the current state thefunction produces an audio file that is saved with the correct name in the correctfolder, fulfilling the recuirements for the playback function. The problem is as thephone it is tested on is restricted, it is not allowed to initiate the "prepare" statewhen starting the recording as the API and phone restrictions prevent the use of"voice call" as mentioned earlier. This results in an empty audio file in the rightposition and with the right name.

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3.5 SearchThe search is based on visual features which is represented by an integer in thedatabase. As such an avatar could be represented by e.g. the series of integers0, 1, 3, 4, 0, etc. The search algorithm works by selecting those numbers whofits the current search series of numbers. The search algorithm also contains aneutral state in which it sends -1 through the algorithm disabling the sorting ofthat particular part. Figure 11 describes a scenario in which three avatars exists inthe database and the user searches for e.g. hair color black represented by the 0 inthe search function. The search algorithm then checks the avatars in the databaseto see if anyone has a 0 in the corresponding position and disables any avatar inthe list who has not got the 0. This ends up resulting in only one avatar in thisscenario.

Figure 11: Search algorithm.

3.6 DatabaseThe database is structured to contain information for each avatar. The list belowdetails which items are saved and in what type of data they are stored.

• Integer index used for easy access

• String name of contact

• String number of contact

• String filepath of the sound that has been saved with the contact

• String filepath of the avatar image saved at generation of avatar

• Integer representing hair style

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• Integer representing hair color

• Integer representing eyes type

• Integer representing mouth type

• Integer representing nose type

• Integer representing jaw type

• Integer representing glasses

• Integer representing skin color

• Integer representing gender

3.7 The Final ProductDuring the implementation there have been made a number of corrections to theconcept design described in the beginning due to some missing features as well asthe results from the usability test performed on the application. The entry screenas described in the design section, still has the same features, though without thenames for the avatars in the grid. For the future the "add avatar" icon needs tobe modified accordingly to the input derived from the usability test. The currentversion of the entry screen is displayed in Figure 12. The next screen is the oneused for creating the avatar. In the concept design it uses only one button foraccessories and one for hair color, using text to add information on the buttons.In the final version this is changed to four buttons with icons on for differentaccessories and features of the avatar. The save button is also changed from thetext "Save" to an icon. The current design of the avatar creation screen is shownin Figure 13. The gender icon and skin color icon was changed due to resultsfrom the usability test. After setting up the avatar you continue to the next screenthat allows you to enter name and number for the contact you are about to addto the contact book. This screen was not design during the concept design, as itswas a small part. The final version is display in Figure 14, it contains a icon ofthe avatar they just created with a field use for entering the name, and below aimage of a numpad with a field for entering the phone number. The next screen iffor viewing information of the avatar. In the concept design of the screen it hadonly three parts, the image of the avatar, a sound button and the button with nameand number of for calling the contact. In the final version it has changed boththe sound button and name and number button to not show as a button. Besidethe sound icon has been changed to a more detailed version. Another change isthe introduction of the delete button next to the sound button, visualized by a red

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Figure 12: A screen-shot of the current version of the entry screen.

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Figure 13: A screen-shot of the current version of the avatar customization screen.

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Figure 14: A screenshot of the screen for entering the name and number of thecreated contact.

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cross. This cross will have to be changed in size as the result of the usability test,where it proved to easy to access by accident, deleting the contact. The currentdesign of the screen is shown in Figure 15. The final screen of the application

Figure 15: Screenshot of the screen containing avatar information.

is the one that manages the search function, allowing one to search through the

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database by using a variety of features. Just like the concept design it containsfour features for searching such as gender, glasses, hair color and skin color. Thewere some changes to the icons as is displayed in Figure 16.

Figure 16: Screenshot of the screen used for searching the database of contacts.

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4 Test Design and Results

4.1 IntroductionIn this chapter there will be a detailing of how each test is structured and designed,and which results the tests gave. It has been split up as voice, avatar and userinterface tests was conducted seperately.

4.2 Voice Recognition TestDuring this section a description of the two low fidelity test and high fidelitytest for voice recognition is given. The first low fidelity test will serve to givea better understanding of identity matching between voice and face, using avatarsfor unfamiliar targets. The second low fidelity test is made in order to investigatethe effect of sound quality on people’s ability to identify voices . The high fidelitytest is done in order to investigate the impact that the relationship between theparticipant and the target has on identification over time.

4.2.1 First Low Fidelity Test

During this section a description of first low fidelity tests is given, this test is con-cerned with voice recognition. The reason for performing this test is in order tofind out how well voice recognition can be used in aiding illiterates navigating acontact book. The first test is regarding voice recognition, for this test a total of16 subjects were tested all students from Aalborg University at the department ofMedialogy, 3 women and 13 men. The test was design to test the participant’sability to recognize unfamiliar voices in relation to an avatar face; therefore thistest was split into two. One section was concerned with voice-to-face recogni-tion with 8 subjects and the other face-to-voice recognition with the remaining 8subjects in order to test both aspects of recognizing a voice from an avatar. Forthe test a range of female and male avatar faces was created as well as a numberof female and male voices was recorded saying the same sentence. These voiceswas recorded using a Samsung Galaxy S2, recording at 44 Khz, the environmentfor the recording was people’s homes, giving the setting that would be the casefor the application. The reason for keeping the sentence the same is in order tokeep focus on the voice, by removing queues that might arise if people say differ-ent sentences. The sentence that is used is "Hvordan har din dag været?" whichtranslates into "How have your day been?".

Test SetupThe test setup is made up of one person controlling the visual feedback to the

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test participant, using a laptop while sitting next to him, and another facilitatorsitting across the table controls the audio feedback. Before each test starts the testparticipant is told that his objective is to remember the avatars and their voicesas for later recall. For both the voice-to-face recognition and the face-to-voicerecognition the test is divided into two sections one containing the female and onefor the male. This test design is inspired by Joassin et. al. [7]. The test participantis first shown 6 female faces with voices, running through them twice in orderfor the participants to familiarize themselves with the avatars and their voices; thesame is done before doing the test regarding the male avatars. The avatars are

Figure 17: Test setup for face-to-voice, dependent on the whether the participantstarts with male or female avatars they begin training with the gender they arechosen to start with, this setup is the same for voice-to-face but revers with 4voices and 1 face.

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named with a number instead of a name; this is done to eliminate any relationthe participant might have to that name, which could help him/her remember. Forthe face-to-voice they are shown 3 sets of 4 faces for male and 3 sets of 4 facesof female, two of the 4 are distracters that they haven’t seen and the other two ishence the target and another of the 6 avatars shown in the beginning. They thenhave to assign the correct face to the one voice that is played. They only hear thevoice once. For the voice-to-face the same setup is used but giving them 4 voicesper set, where they have to recognize the correct voice that belongs to the oneavatar face that they are shown per set. For both face-to-voice and voice-to-facethere are 4 subjects that start with the male targets first and the last 4 subjects startwith the female targets. The order by which these sets are organized is randomizedin order to rule out any pattern that might become visible for the participant. Avisualization of the test setup can be seen in Figure 17. In Figure 18 a simple

Figure 18: Physical test setup.

sketch is given of how the test setup was done. As the facilitator sitting next to thetest participant was showing the visual feedback in form of the avatars, the avatarswas organized in files using unrelated names preventing them from relating namesbetween the first shown targets and the sets of 4 avatars in the case of face- to-voicerecognition. These files are arranged in the test order so that the two facilitatorshad a simple pattern to follow. Each time the test participant utters the avatar orvoice that he/she claims to be the correct one, the result is noted by the facilitatorsitting across the table in an excel ark. The entire test setup and results can befound in an excel ark on the attached DVD.

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Test Results: Voice to Face RecognitionIn these diagrams, Figures 19, 20 and 21, the "wrong-distractor" means that thetest participant has made a wrong recall by identifying a distractor. A "wrong-tar"means that the participant has identified a previously seen/heard avatar, one of the6 avatars shown with in female and male.

Figure 19: Female avatars: voice to face. (23 correct, 1 wrong-distractor, wrong-tar 0)

Figure 20: Male avatars: voice to face. (20 correct, 4 wrong-distractors, wrong-tar0)

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Figure 21: Female/male avatars: voice to face. (43 correct, 5 wrong-distractors,wrong-tar 0)

Test Results: Face to Voice RecognitionIn these diagrams, Figures 22, 23 and 24, the same applies as for the previousdiagrams, except that this if for the face-to-voice test.

Figure 22: Female avatars: Face to voice. (21 correct, 0 wrong-distractor, 3wrong-tar)

Part ConclusionWhen looking at the data from the voice to face test and the face to voice test for

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Figure 23: Male avatars: Face to voice. (20 correct, 0 wrong-distractor, 4 wrong-tar)

Figure 24: Female/male avatars: Face to voice. (41 correct, 0 wrong-distractor, 7wrong-tar)

recognition of voices, an interesting pattern emerges. When the test participants inthe voice to face test perform a wrong recognition they recall a distracter. On theother hand when participants in the face to voice test perform an error they recall apreviously seen target which is not the target for the voice they were told to recall.Although there is this difference when performing errors, the general error rate islower than 20% and lowest for the voice to face. The fact that the test participantsin the face-to-voice test choose a previously seen target when choosing wrong

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could indicate that the information from the faces is easier recalled. In contrast,in the voice-to-face test, they never choose a previously heard target when failingto recall the target; this shows that the participants find it harder to recall voicesthan faces. Keeping this in mind, the voice-to-face had a lower error rate than theface-to-voice.

4.2.2 Second Low Fidelity Test

The focus of this test is to find how big the impact of sound quality is on people’sability to match identity from recorded unfamiliar voices. The reason for this isthat not all phones purses the same sound quality when hearing the caller throughthe phone or on loudspeaker. The voices used in this test are the same as recordedfor the first low fidelity test. As this test is for finding the impact of sound quality,the recorded samples have to be down sampled to a lower quality for the test. Thisis done through Audacity where the files are saved in an mp3 format at a lowersample rate. The three different qualities that is tested are 8, 24, 32 Kb/s with theoriginal being 44 Kb/s from the Samsung galaxy S2. As the audio is taken fromthe first low fidelity test, the sentence spoken is the same "Hvordan har din dagværet?".

Test SetupIn this test the test participants will have to identify different voices, played atdifferent qualities. To eliminate the effect of different genders, the voices thatwill be identified are arranged in a group of male voices and one with femalevoices. The test is arranged as a within subject test, each subject will be exposedto each sound quality within both male and female voice, at each position in thesets. The table below in figure 25 shows the organization of the male and femalesets with the three different qualities. As is seen in figure 25, there are 9 setsof male and female voices. For the training before the test they are familiarizedwith 6 voices of men and then females. These voices are not given a name buta number, just as in the first low fidelity test. For both men and female there are3 targets out of the 6 voices, each played with the three sound qualities and witheach quality at a different position in the order of play. Together all the male andfemale targets ensure that each quality at one point is played in each position. Fora better visualization of the test procedure a flow chart is created, this can be seenin figure 4. Each test participant is trained with 6 female/male voices twice, withineach set as shown in figure 25. In each set there is the target voice, a distractorand previously heard voice, which is one of the 6 voices that are not targets. Asis seen in figure 26 the test participant is trained in first 6 male voices and thentested, then trained in the 6 female voices and tested with those. The physical testsetup was with one person playing the sounds from a laptop and a facilitator that

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Figure 25: The organization of the sets for both male and female voices. The L,M and H is the different qualities of sound. L = 8 Kb/s, M = 24 Kb/s, H = 32 Kb/s

noted down the answers of the test participant as well as any expressions by theparticipant.

Test resultsFor this test a total of 10 participants were tested, all male. To get an understandingof the effect of quality, a point for each correct answer is awarded. All point foreach quality is summed up for a value reflecting each qualities success rate.

• High (H) = 51 correct (85%)

• Medium (M) = 46 correct (76.7%)

• Low (L) = 42 correct (70%)

The reason for the relative small difference might be due to characteristicsof the voices used, but this reflects what you would encounter in the real worldas people talk with different amplitude, punctuation and more. It has not beenpossible to find the cut off quality where it is no longer recognizable, but a graphdepicting the tendency is shown in figure 27. As is seen in the graph in Figure 27,it is possible to see a downward tendency assuming that a quality of 0 Kb/s isequal to no recognition. Given the high percentage of success rate it can be said

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Figure 26: A flow chart of the test procedure for the test participants

that it is possible to lower the sound quality to 8 Kb/s and still have a success rateof 70%.

4.2.3 High fidelity test

During this test, the hypothesis will be answered. The goal is to investigate theimpact of the relationship between the participant and the voice they are trying toidentify, over time. The hypothesis is displayed below.

• Null hypothesis: when matching identity from audio input there is no dif-ference over time between participants that are familiar with the targets andthose who are not.

• Alternate hypothesis: when matching identity from audio input there is adifference over time between participants that are familiar with the targetsand those who are not.

The audio stimuli used in this test is retrieved in two different ways as one groupof the test participants is tested with familiar voices and the other group withunfamiliar voices. The group with unfamiliar voices will hear the same voicesthat were recorded for the low fidelity tests, recorded with the Samsung Galaxy

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Figure 27: A graphical representation of the data from the three different qualities,the y axis is the percentage of correct answers, and the x axis is the quality of thesound. This graph assumes that a quality of 0 Kb/s equals no recognition

S2. The group with the familiar targets will have to call 4 friends or family overthe phone. The phone is then put on speaker and the friend or family member willsay the same sentence as for the unfamiliar that is "Hvordan har din dag været".This is then recorded on the Samsung Galaxy S2. By having them speak overthe speaker we get the worst case scenario for sound quality as it is lower qualitythen the audio directly from the phone. This causes a difference in sound qualitybetween the audio for the group with unfamiliar targets and those with familiartargets, which has to be taken into account.

Test setupThe test is divided into two; one group of the test participants is tested with un-familiar targets and another with familiar targets. For both groups the test is atwo part test, the first day the participants are familiarized with the targets throughhearing all voices 5 times. Each participant is trained on 4 targets, 2 male and 2female, familiar or unfamiliar. For familiar this was not always the case as it wasnot always possible to reach 2 male and female friends or family at the time ofrecording. Two days later the participant is tested for his/her ability to identify thevoices. The test is a within subject test, each participant is run through 14 sets,2 of them with no targets in. Each target is rotated around so it is placed at allpositions at one point. Each set contains three voices 1 which is the target andtwo distractor voices. Each time the test participant has been presented with the 3voices, he/she will tell at what location the person is that they recognize and that

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person’s name or number. The group with familiar will use the name of the personand the group with unfamiliar target the number of the person. A visualization ofthe test design is displayed below in figure 28. When recording the voices for the

Figure 28: A flow chart of the test design for the high fidelity test.

group with familiar targets, it was not always possible to attain 2 female and 2male voices of their friends or family. This meant that some test participant hadonly men and others a mixture. The physical test setup was placed in a room atAalborg University. One person handled playing the audio in the correct order ac-cording to the sets, and the other noted the results while taking notes of occasionalremarks from the test participant. After identifying the voices in the 14 sets, thetest participant is asked to answer a questionnaire as displayed below. The twofirst questions are related to the group with familiar targets.

• Name:

• Have you talked with any of the subjects from the first part of the test sinceit was recorded?

• If you have, how often and how long?

• What helped you recognize the voices?

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• What proved hard to recognize and why?

These questions are asked to get a understanding if the participants in the groupwith familiars has talked with the targets in the two day period and if how often, asit might not be possible for them not to talk to them. The remaining two questionsare asked to try and figure out what they attend to when identifying the target. Thequestionnaires and excel arks containing the test setup and results are possible tofind on the attached DVD.

Test results and discussionTo verify or reject the null hypothesis a T-test is performed on the data. TheT-test is a two tailed T-test with one group of data from the participants withunfamiliar targets and the other with participants with familiar targets. The resultof the T-test is displayed below in figure 29. As is seen in figure 29 the p value

Figure 29: The data from the T-test.

is below 0.05 meaning that the null hypothesis is rejected, thereby accepting thealternate hypothesis. This shows that there is a significant difference between thetwo groups, showing that the test participants are significant better at identifyingthe voices from familiars than unfamiliar.

By looking at the questionnaires it is possible to see that one of person from thegroup tested on familiar targets did not hear the targets voice in the two day period.This might improve the difference between the two samples. At the same time thevoice recorded for the group using familiars, was of poor quality compared to thequality of the unfamiliar group. The recording of the voice from the speaker of aphone meant that the quality was low compared to recorded audio direct from thehuman voice. But as they were able to recognize the voices even though the lowerquality, strengthens the result of the familiar group being better at identifyingthe voices. The one person that did not talk with any of his friends and familyrecorded for the test had a success rate of 100%. To get a better description ofthe relationship between the two samples, familiar and unfamiliar and the effectthe two days had, another t-test is performed only using the targets that the test

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participants had not talked with over the two day period. The result of this t-testis shown in Figure 30.

Figure 30: The t-test results when only using the targets not talked to during thetwo days period

As is seen in Figure 30, the probability is even smaller when using only thetargets that were not spoken to during the two day period. This confirms that theconclusion made using all the data also applies for the reduced data with onlytargets not talked to. This shows that there is a significant difference betweenfamiliar and unfamiliar showing that the familiar are better at recognizing thetargets over a three days period.

As is concluded above, there is a significant difference between the group withfamiliar and unfamiliar targets, proving that the group with familiars performedsignificantly better. To get a better overview of the precision within both groups,the success rate in percentage is displayed below.

• Group with familiar targets: 97.24 percent

• Group with unfamiliar targets: 69.04 percent

Even though the group with unfamiliar did not know the targets they still per-formed above chance at a success rate of 69.04 percent. With familiar targets thesuccess rate is 97.24 percent giving an almost 100 percent accuracy, showing thatthis function is usable as a feature for recognizing contacts on a phone.

From the questionnaire a number of different features were given that helpedthem recognize the voices when tested. What helps the test participants accord-ing to the questionnaire is the Pitch, Emotions, Background noise cues, accent,Volume, pronunciation, small errors when pronouncing the sentence, rhythm andquality differences. The features that the test participants found most helpful wasthe pitch, pronunciation, background cues. To better visualize the results fromthe questionnaire, a diagram is created showing how important the feature is. Thediagram in figure 31, is a result of counting how often each feature is mentionedwhen answering "What helped you recognize the voices?". As is seen in figure

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31, the most important features are pitch, pronunciation and background noisecues. The fact that there was a difference in quality can have biased the results,

Figure 31: Diagram of the occurances of the different features when answeringthe question "What helped you recognize the voices?"

both in the sense that it could prove harder to recognize the voice and that it wouldbe easier to eliminate the distractors.

4.3 Avatar Recognition Test

This chapter explains the design and method of the two tests which used visualavatars. The first test was used to determine if the approach from face recognitionknown as holistic perception also worked with virtual cartoon characters faces.The second test was about recalling avatars presented in three different ways overa two day period of time. In the end of this chapter a discussion will explain theresults from the tests.

4.3.1 Low Fidelity Test

There have been a lot of research regarding how humans perceive and understand aface but not if this research also works for virtually created avatars which only hasfeatures that resembles human features. This first test was a test to see if feature-specific perception or holistic perception would be strongest with virtually created

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avatars. The design of the test follows that of Belle et. al. [2] in which the par-ticipants was shown a face masked at certain locations to enable feature-specificperception or enable holistic perception. An example of this can be seen in fig-ure 32. Then in a mix of distractors and previously shown faces the participants

Figure 32: Example taken from [2]

Figure 33: An overview of the test setup of the avatar low fidelity test

would have a very short amount of time to decide which of the faces they had seenbefore, if any. Our test used this test as a starting point by also having the partici-pant seeing 6 avatar faces in a series which the participant then had to remember,an overview of the test setup can be seen in figure 33. The series was shown 3times in which each avatar had around a 2 second period. After this rememberingpart the participant was shown another series of 6 avatars masked accordingly toeither feature-specific recognition, see figure 34, or holistic perception recogni-tion, see figure 35. Each participant would receive 12 of these series in which

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Figure 34: A sequence from a participant who was shown feature-specific maskedavatars.

Figure 35: A sequence from a participant who was shown avatars masked to fit aholistic approach to face recognition.

they would have to find one of the previous remembered avatars in a mix of pre-vious seen avatars and distractor avatars which they had never seen. The testerwould ask the participant to find e.g. Avatar 1 from the remembered set, makingthis a recall task in which they had to remember each avatar by a number and theavatar visual features. In total 8 participants had the feature-specific, 4 had malewhile the other 4 had female avatars, and 8 participants had the holistic approach,half and half on both male and female avatars again. In figure 36 a brief overviewof the test setup can be seen. The hypothesis for this test was to find out if the

Figure 36: 1) Test facilitator changed images on screen. 2) Participant. 3) Screen.

holistic percept is more important in avatar recognition than the feature-specificapproach. The results rejects the hypothesis as the participants who were testedwith the holistic approach did not have any significant differences compared tothe ones tested with the feature-specific approach, the correct answers per groupwere used as data and the P value for the test is 0.053. A summarization of thenumbers used can be seen in table 2. Further information about results and notesduring the test can be found in appendix "Facial Recognition.xlsl"which contains Write the cor-

rect "link" tothe file andname

the raw data from the test.

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Feature-Specific Holistic Approach

Correct Failed Correct Failed75 21 85 11

Mean Correct Percent Correct Mean Correct Percent Correct9.25 78.1% 10.125 88.5%

P-Value 0.053

Table 2: Correct and failed answers from the two groups.

4.3.2 High Fidelity Test

This test was designed to see if there is a difference in the ability to rememberan avatar over time if you had a certain level of familiarity with the subject youmade an avatar for. The test included three different groups, a control group,an unfamiliar group and a familiar group. The control group was supplied withpre-made avatars from the application the other groups would use to generate andcustomize their avatars with. Each participant would be presented with two fe-male and male avatars which they would have to remember over a period of twodays at which point they would have to point out which avatar they remembered,much like the first test except here they would not be asked to find a certain avatarbut just tell if they found one they remembered and the number associated withit. This time it was 16 sets of four avatars that included distractors, multiple cor-rect targets and one set that only had distractors in it. In figure 37 an example ofwhat participants in the control group would have to remember can be seen. In

Figure 37: An example of what participants in the control group would have toremember.

the unfamiliar group the participants was supplied with photos of two women andtwo men which they would have to make an avatar from and remember them overthe same time period as the control group. This group also had 16 sets of fouravatars that included distractors, multiple correct targets and one set that only haddistractors in it. This group was used to see if the act of creating an avatar for an

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Figure 38: An overview of the test setup of the avatar high fidelity test

unfamiliar person would increase the accuracy of the memory or if it would bethe same as the control group. In the familiar group it was the same procedureas the unfamiliar group, except the photos would be of two female and two malefriends of the participant which, together with the participant, was found on face-book. The participant was instructed to create an avatar that resembled the personas they remembered the person and not as they looked on the profile picture onfacebook. The name, picture and avatar was recorded as they would have to recallname and avatar at the later stage. This group was used to determine if a personwas familiar, we categorized familiar as a good friend or family, it would be easier

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to remember and as such the accuracy would be higher than the other groups. Anoverview of the test setup for this test can be seen in figure 38.

As such we end up with three hypotheses for this test:

1. The unfamiliar group has a higher accuracy than the control group.

2. The familiar group has a higher accuracy than the control group.

3. The familiar group has a higher accuracy than the unfamiliar group.

The results from the test can be summarized as seen in Table 3. As seen each hy-pothesis has some support by a difference of at least 10% in correct targets whichis also shown to be significantly different through a t-test as shown in Table 4.The concept behind correct position is if the participant found the correct posi-tion of the target but could not remember which avatar corresponded. This wasclearly a problem with the control group in which one subject switched aroundall the avatars but still got 18 positions correct. Adding the correct positions to-gether with the correct targets delivers a new set of values in which the controlgroup actually scored higher than the unfamiliar group. This could also supportthat when you create the avatars yourself you are in a better position to rememberthe associated name or number, because you associate the picture or person withthe avatar. A graph showing the correct answers by group is shown in Figure 39.

Control Group Unfamiliar Group Familiar GroupParticipants 8 8 8Total Targets 160 160 160

Correct Targets 111 127 145Correct Position 28 1 0

Percent Correct 69.38% 79.38% 90.63%Percent Correct Position 86.88% 80.00% 90.63%

Table 3: Summarization of results from the second test.

After each run through of the sets each participant was also asked which featuresmade it easier to remember the avatars and remember the differences betweeneach avatar. Out of the 24 participants 20 used hair color and style to differentiatewhile eyes, chin/face build, mouth, glasses and nose had 5-6 participants usingthem to differentiate. This separates hair as the primary source that helps separatethe avatars from each other.

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Figure 39: A graph showing correct answers through groups.

T-Test Groups Control Group Unfamiliar Group Familiar GroupMean Correct Answers 13.88 15.88 18.13

Mean 0.693 0.793 0.906Variance 0.213 0.164 0.085

P-Value Control-Unfamiliar 0.0406

P-Value Control-Familiar 1.55788E-06

P-Value Unfamiliar-Familiar 0.0047

Table 4: T-Test for the second test.

4.3.3 Discussion

The tests supports that feature-specific perception and holistic perception alsoworks with avatars as a means of understanding and remembering the avatar. Inthe test some participants also noted that they thought the avatar felt somethingor looked like they were in a certain mood, giving social meaning to a virtualface. This could be because humans are hardwired to see and understand thisdeeper social meaning from facial features as shown in the chapter describing fa-cial recognition theory. Because of this, the participants in the second test who

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had to make their own avatars also gave each avatar an expression that would showa certain state of mind as they perceived that person. Multiple participants alsonoted that they could remember through different mouth types, ones that lookedhappy, satisfied or disagreeable. In the second test the results show that a higherpercentage accuracy can be retrieved when the participants use familiar subjectsto create the avatars from. A reason for this could be that they use more time tocreate the avatars, but so does the unfamiliar group. Multiple participants that cre-ated their familiar persons was also noted to be laughing when creating the avatarsat certain points because of the avatar designs as some of them was unexpectedin the application. This, as a form of play, could increase the persons accuracy inremembering which the test results supports. So adding play in the form of avatarcustomization increases accuracy over a two day period compared to a controlgroup that did not get to play with the avatar customization. Adding the conceptof using familiar subjects further increases the accuracy, giving increased sup-port to the idea of having a contact book that builds on the idea of having avatarcustomization.

4.4 High Fidelity Test of InterfaceThe contact book created in this project is oriented towards illiterates, trying todeal with the problems that illiterates have when trying to use the contact bookof a mobile. The purpose of this test is to investigate if the interface is workingas intended; this is done with an usability test. The target group of this project isilliterates, but due to the circumstances it was not possible to find illiterate peopleto test the interface on. Instead a number of literate people are used for the test totest the usability of icons and functions. This can help adjust potential errors thathave been made. The fact that the test participants are not illiterate might result inlag of important input, as illiterates have certain tactics they apply when dealingwith contact books of phones [1]. To simulate the situation that illiterates are in forthe literate test participants, text is changed into Chinese symbols, forcing themto rely on the icons.

4.4.1 Test setup

The usability test is divided into two sections, in the first the participant has tocarry out a number of assignments and last answer a short questionnaire. Whenthe test participant enters they will be explained the process, that they first haveto carry out a number of tasks on the app, followed by a short situated interview.Beside the test participant there is one facilitator in control of the tasks and an-other facilitator noting the test participant’s actions during the tasks. When theparticipant is given the tasks he/she is told to think aloud, telling what they will

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do in order to follow their thought process and actions. After completing the tasksthe test participant is asked a number of questions to follow up on the tasks theyperformed. Below in figure 40 is a visualization of the test design. The test is

Figure 40: The structure of the usability test

performed as an iterative process, after each test participant has been tested, themost prominent error is changed to accommodate the participants input. This isdone to find as many flaws as possible. The tasks that the participants are givenduring the test, is displayed below.

• Create a new contact (Female, blond hair, long hair, green eyes, glasses)with the phone number 38651942.

• Locate the contact in the contact book (to check if they use the search func-tion).

• Use the search function to locate the contact (and enter for information).

• Play the voice of the contact.

• Call the contact.

• Delete contact.

Before the test participants are given the app to perform the tasks on, the contactbook has been filled with a number of contacts both male and female. This is done

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to simulate a more realistic use of the contact book already containing contacts.The tasks presented above are made in order to test the different aspects of thecontact book with regard to functionality and icon design. Followed by the task isthe interview, below is the questions asked in the interview.

• Gender.

• Age.

• What did you find difficult and why?

• What could be improved and how?

• What would you use the app for, in what situation or case?

The first two questions are asked to get information about the participant, the nexttwo is asked to locate potential problems and suggestions for improvement. Lastlya question to get a more broad aspect of the app, even though the test participantsare not illiterates it can help understand in what other situations this app could beuseful.

4.5 Test ResultsIn the test there were three subjects that participated in the test, all students fromAalborg University. The test was carried out at Aalborg University. During thissection each subjects test result is presented and the changes that was made inorder to get a better view of the results.

4.5.1 Subject 1: Male, 25

Create a new contact (Female, blond hair, long hair, green eyes, glasses) with thephone number 38651942: During this task the subject found the button for addinga new avatar on his first try. When creating the avatar he plays around with thebuttons on the side to figure out what part of the avatar it changes. For the laststage of the creating the avatar where the name and number has to be entered, heunderstands the symbols for them and enters the correct and saves using the diskicon.

Locate the contact in the contact book (to check if they use the search func-tion): When presented with this assignment he chooses the button with an avatarand a loop over because it to him represent search.

Use the search function to locate the contact (and enter for information): Firsthe just scrolls down through the contact book without using the search function,

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but when told to use the search function he starts the search by choosing glassesas a feature in the search. He miss understands the icon for gender for beingsomething related to the hair. He enters the contact by pushing on the windowcontaining the avatar.

Play the voice of the contact: Uses the correct sound icon as his first choice.

Call the contact: Pushes the phone number to call the contact on his first try.

Delete contact: Pushes the cross to delete the contact on first try.

4.5.2 Subject 2: Male, 24

Create a new contact (Female, blond hair, long hair, green eyes, glasses) with thephone number 38651942: When trying to create a new avatar he instead pushesone of the contacts and when trying to return he pushes the cross and therebydeleting the contact. On his next try he pushes the right button. When creating theavatar he utters that the icon for the glasses should be more clearly displayed.

Locate the contact in the contact book (to check if they use the search func-tion): First the participants just look through the contact book, thinking he foundthe contact but was not the correct one. On his second attempt he uses the searchfunction.

Use the search function to locate the contact (and enter for information): Firsthe starts by scrolling down, instead of using the search features. When told to usethem he uses them flawless.

Play the voice of the contact: Uses the speaker icon.

Call the contact: Uses the phone number as button.

Delete contact: Uses the cross button.

4.5.3 Subject 3: Male, 24

Create a new contact (Female, blond hair, long hair, green eyes, glasses) with thephone number 38651942: This subject has tried the creating section of the appbefore so performs the entire task correct when creating the avatar.

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Locate the contact in the contact book (to check if they use the search func-tion): He uses the button with the loop on as he utters, to search for the contact.

Use the search function to locate the contact (and enter for information): Thissubject is the first that uses the search features in first try, instead of scrolling asthe two previous subjects.

Play the voice of the contact: Uses the correct button for the task.

Call the contact: Uses the correct button for the task.

Delete contact: Uses the correct button for the task.

4.5.4 Main Findings from Subjects

Even though it was not possible to test on illiterates, the test of the interface withliterates proved to give some useful information about general changes in the de-sign of the interface. For a more case relevant usability test, a test is needed withilliterates, in order to understand their needs and the effect of the strategies theyapply when using technologies like mobile phones. In general subject 1 performedwith few errors during the tasks, he understood the way of creating avatars wellwith no troubles at understanding the functionality and icons within that area. Theonly icon that he didn’t understand was during the search task, which was the iconfor gender that was thought to be related to something with hair. During the in-terview he told that some of the icons in the search was not logical, especiallythe one with the gender as was also found in the tasks. He suggested using thesymbol for men and women instead. Beside the button with the gender, he wouldhave liked if a cross had applied to the glass icon when the glasses was removedfrom the search. For the creation of the new avatar, he utters that a small greenplus sign would had helped him recognize faster that it was the "add new avatar"button. Last he explained that the arrows used when switching among differentfeatures when creating the avatar, should be more outstanding. When thinking ofcases where this way of ordering your contact could be used, he thinks of peoplewith a huge network. The reason for this as he explains is that it might be difficultto remember all the names of who is who, so could be smart to search by visualappearance instead.

Contrary to subject 1, subject 2 does not get the first attempt right when tryingto create an avatar and miss interpreting the cross as an exit button. Contrary tosubject 1 he only says during the test that the glasses should be clearer when creat-ing the avatar. Just like subject 1 he does not start out by using the search functionwhen trying to locate the contact, but first in second attempts. But when used it

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was used flawless. The fact that both subjects do not locate the search featureswhen searching for a contact indicates that the search function has to be more vi-sually noticeable. He uses all the icons within the contact correct, due to the factthat he found the cross to delete a contact earlier. During the interview explainsthat just like subject 1 that the "create new avatar" was difficult to understand andthat a green plus symbol would help him understand this. The reason why he usedthe Red Cross as a return button was due to his lack of experience with android.He explained that it would be easier for him to understand the delete icon, if itwas visualized as a garbage can. This icon might prove to be more universal thanthe cross. Subject 3 performs perfectly in the creation of the avatar as he has triedit before and generally uses the correct icons for the tasks. He is also the first thatuses the search function correct on first try. During the interview he expresses thatit would be nice with an indicator that shows how far you are in the list of features.Beside this the skin color icon could be improved with having a face with color oninstead. When navigating the interface of the contact, he explains that it would bebetter to have a smaller delete icon as he might accidentally hit it and deleting thecontact as it is placed next to the sound button. The size of the delete button needsto be changed to reduce the risk of deleting a contact by accident. When askedof what other cases or situations this could be useful for, he explains that it mightbe useful for children that cannot read yet. This could be an interesting aspect tolook into. As described above there are a number of features and icons that needsto be changed to further improve the contact book, keeping in mind that it needsto be further improved with regards to illiterates. In general the interface provedusable as the participants were able to navigate and use the functionalities withfew errors. As any new interface there is always a learning curve that will causesome flaws when trying to use the functionality of the contact book.

4.5.5 Conclusion

Even though it was not possible to test on illiterates, the test of the interface withliterates proved to give some useful information about general changes in the de-sign of the interface. For a more case relevant usability test, a test is needed withilliterates, in order to understand their needs and the effect of the strategies theyapply when using technologies like mobile phones.

References

[1] Syed Ishtiaque Ahmed, Maruf Zaber, and Shion Guha. Usage of the memoryof mobile phones by illiterate people. DEV’13, 2013.

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[2] Goedele Van Belle, Peter De Graef, Karl Verfaillie, Thomas Busigny, andBruno Rossion. Whole not hole: Expert face recognition requires holisticperception. Neuropsychologia, 48:2620–2629, 2010.

[3] Salvatore Campanella and Pascal Belin. Integrating face and voice in personperception. Trends in cognitive science, 11(12), 2007.

[4] A. Castro-Caldas, K. M. Petersson, A. Reis, S. Stone-Elander, and M. Ingvar.The illiterate brain: Learning to read and write during childhood influencesthe functional organization of the adult brain. Brain, 121:1053–1063, 1998.

[5] Brian R. Clifford. Voice identification by human listeners: On earwitnessreliability. Law and Human Behavior, 4(4), 1980.

[6] Kristin Dew, Carin Fishel, and Muna Haddadin Apurva Dawale. Karaoke:An assistive alternative interface for illiterate mobile device users. CHI2013: Changing Perspectives, 2013.

[7] Frédéric Joassin, Mauro Pesenti, Pierre Maurage, Emilie Verreckt, Ray-mond Bruyer, and Salvatore Campanella. Cross-modal interactions betweenhuman faces and voices involved in person recognition. Elsevier Cortex,47:367–376, 2011.

[8] Robert G. Franklin Jr. and Reginald B. Adams Jr. What makes a face memo-rable? the relationship between face memory and emotional state reasoning.Personality and Individual Differences, 49:8–12, 2010.

[9] Patricia K. Kuhl. Who’s talking? Science AAAS, 333(529):367–376, 2011.

[10] Zereh Lalji and Judith Good. Designing new technologies for illiterate pop-ulations: A study in mobile phone interface design. Interacting with Com-puters, 20:574–586, 2008.

[11] Karen Lander, Harold Hill, Miyuki Kamachi, and Eric Vatikiotis-Bateson.It’s not what you say but the way you say it: Matching faces and voices.Journal of Experimental Psychology: Human Perception and Performance,33(4):905–914, 2007.

[12] Frances McGehee. The reliability of the identification of the human voice.The Journal of General Psychology, 17(2):249–271, 1937.

[13] Indrani Medhi. Building interfaces for the illiterate, 2010.

[14] Rochelle S. Newman and Shannon Evers. The effect of talker familiarity onstream segregation. Journal of Phonetics, 35:85–103, 2007.

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[15] Yueting Sun, Xiaochao Gao, and Shihui Han. Sex differences in face genderrecognition: An event-related potential study. Brain Research, 1327:69–76,2010.

[16] A. Thatcher, S. Mahlangu, and C. Zimmerman. Accessibility of atms for thefunctionally illiterate through icon-based interfaces. Behaviour & Informa-tion Technology, 25(1):65–81, 2006.

[17] Steven G. Young, Kurt Hugenberg, Michael J. Bernstein, and Donald F.Sacco. Perception and motivation in face recognition: A critical review oftheories of the cross-race effect. Personality and Social Psychology Review,16(2):116–142, 2012.

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